It's just a version of a model i made which predicts stocks, when I run it, it works fine, but returns errors with the output, note indentations were messed up but its self explanatory
This is the code:
import yfinance as yf
from sklearn.linear_model import LinearRegression
start_date = "2000-01-01"
end_date = None
model = LinearRegression()
tickers = ("AMZN","AAPL","TSLA")
for stock_symbol in tickers:
stock_data = yf.download(tickers = stock_symbol, start=start_date, end=end_date, interval = "1d")
model.fit(stock_data[['Open', 'Low', 'Close', 'Volume']], stock_data['High'])
today_data = yf.download(stock_symbol, period="1d", interval="1d")
today_features = today_data[['Open', 'Low', 'Close', 'Volume']]
predicted_high_tomorrow = model.predict(today_features)
if float(predicted_high_tomorrow) > float(today_data["High"]):
status = "BUY"
else:
status = "SELL"
today_high = today_data["High"]
print(f"{stock_symbol} {today_high} {predicted_high_tomorrow} {status}")
It returns the correct output, aswell as some errors: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated FutureWarning: Calling float on a single element Series is deprecated and will raise a TypeError in the future.
